The additive and cooperative relationships between neuromuscular risk factors for anterior cruciate ligament (ACL) injury among young, female athletes are currently unknown. Additionally, there are currently no easy, clinical tests that predict the presence of ACL injury risk factors in athletes. The continued existence of these gaps hinders the effective and widespread prevention of ACL injuries. As a physical therapist with doctoral training in orthopaedic biomechanics my long-term goal is to use my expertise in measuring, interpreting and re-training human motion during functional activities to improve the understanding of ACL injury etiology and develop effective and efficient injury prevention programs. We will use latent profile analysis, a rigorous multivariate approach that allows identification of subgroups in large cohorts, to test our central hypothesis that female athletes a high risk of ACL injury exhibit risk profiles consisting of more than one deficit and that simple clinical measures can be used to identify specific neuromuscular deficits in high- risk athletes. The objective of the proposed research project is to identify the most common risk profiles for ACL injury and to develop simple clinical measures that accurately classify athletes with neuromuscular deficits. The rationale is that existing ACL injury prevention programs may be improved by focusing on the most common ACL risk profiles or by using simple clinical tests to identify specific deficits in athletes and prescribe individualized exercise programs. The hypothesis will be tested by pursuing two specific aims: 1) Identify the most common risk profiles for ACL injury in female athletes using latent profile analysis and 2) Identify simple clinical tests that predict neuromuscular deficits known to increase ACL injury risk in female athletes. This proposal is highly innovative in that: a) it will use rigorous biomechanical data collected during an unanticipated cutting task that may more accurately represent real athletic situations than the more commonly used highly controlled landing tasks, b) it will link neuromuscular deficits identified by the gold standard biomechanical data to easy and simple clinical tests that may be used to screen athletes and subsequently enroll them into quick, specific and efficient injury prevention programs, c) it provides a unique opportunity for the identification of the most common risk profiles because of the large number of enrolled athletes (N=837), and d) it will use a novel methodological approach (latent profile analysis) to classify individuals into subgroups based on similarities on a number of biomechanical variables. The proposed research is significant because it will greatly enhance our understanding of the connections between ACL injury and neuromuscular deficits and because it will advance the field of ACL injury research by providing knowledge that will inform the development of improved injury prevention programs.